20 September 2007 Stability of the multifractal spectra by transformations of discrete series
Author Affiliations +
Abstract
In this work we use α-bi-Lipschitz transformation of signals both from empirical and theoretical sources to obtain new tests for the accomplishment of the multifractal formalisms associated with many methods (Wavelet Leaders, Wavelet Transform Modulus Maxima, Multifractal Detrended Fluctuation Analysis, Box Counting, and other) and we give improvements of the present algorithms that result numerically more trustworthy. Moreover the multifractal spectrum does not change in the theory, but as the numeric implementation of the computations may differ for discrete series so we can analyze its variation to study the stability of the proposed algorithms to compute it. In addition some single coefficients that have been proposed to quantify the whole irregularity of the signal are preserved by enough high α-bi-Lipschitz transformations. We exhibit the performance of the tests and the improvements of this methods not only in signals generated from deterministic (or sometimes random) numerical processes performed with the computer but also against series from empirical sources in which the multifractal spectrum and the irregularity coefficient were proven of utility both from the analysis and the segmentation of the signal in significant parts as series of Longwave outgoing radiation of tropical regions (and the consequent forecasting applications of precipitations) and certain series of EEG (from patients with crisis of brain absences for instance) and the ability to distinguish (and perhaps to predict) the beginning of the consecutive stages.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Corvalán, A. Corvalán, E. Serrano, E. Serrano, } "Stability of the multifractal spectra by transformations of discrete series", Proc. SPIE 6701, Wavelets XII, 670128 (20 September 2007); doi: 10.1117/12.733317; https://doi.org/10.1117/12.733317
PROCEEDINGS
8 PAGES


SHARE
RELATED CONTENT

Artifact removal for physiological signals via wavelets
Proceedings of SPIE (August 28 2016)
Texture analysis of hippocampus for epilepsy
Proceedings of SPIE (May 01 2003)
Wavelet and fractal analysis of ground-vehicle images
Proceedings of SPIE (October 22 1996)
Estimation of a semiparametric model of fMRI data
Proceedings of SPIE (December 04 2001)
Nonuniform spatially adaptive wavelet packets
Proceedings of SPIE (December 03 2000)

Back to Top